Selected Papers from SCIS & ISIS 2010 – No.1

2011 ◽  
Vol 15 (7) ◽  
pp. 813-813
Author(s):  
Keigo Watanabe ◽  
Kazuhiro Ohkura ◽  
Kiyotaka Izumi
Keyword(s):  
Neural Networks ◽  
Evolutionary Computation ◽  
Soft Computing ◽  
Intelligent Systems ◽  
Fuzzy Theory ◽  
Multi Agent Systems ◽  
Special Issue ◽  
Convention Center ◽  
Multi Agent ◽  
Institute Of Technology

SCIS & ISIS is a biennial international joint conference on soft computing and intelligent systems, with research ranging from fuzzy systems, neural networks, and evolutionary computation to multi-agent systems, artificial intelligence, and robotics. SCIS & ISIS 2010 consisted of the 5th International Conference on Soft Computing and Intelligent Systems (SCIS) and the 11th International Symposium on Advanced Intelligent Systems (ISIS), held at Okayama Convention Center on December 8-12, 2010. Original presentations numbered 302 and participants 322. After preliminary selection by SCIS & ISIS 2010 session chairs, we listed over 70 papers to be published in extended form in the Special Issue of the Journal of Advanced Computational Intelligence and Intelligent Informatics. After inviting these authors to submit papers for this special issue, we had two referees to review them and accepted 27 for publication in Vol.15, Nos.7 and 8 in 2011. This special issue presents 15 of these papers covering most conference topics, including fuzzy theory, learning methods, neural networks, and evolutionary computation, with a focus on reinforcement learning, multi-agent system, nonlinear estimation, and real-world applications to visual system, robotics and energy. We thank the authors and reviewers for their invaluable contributions toward making this special issue possible. We are also grateful to Editors-in-chief Prof. Toshio Fukuda of Nagoya University and Prof. Kaoru Hirota of the Tokyo Institute of Technology for inviting us to serve as Guest Editors.

Selected Papers from SCIS & ISIS 2006 – No.1

2007 ◽  
Vol 11 (6) ◽  
pp. 535-535
Author(s):  
Naoyuki Kubota ◽  
Keyword(s):  
Neural Networks ◽  
Soft Computing ◽  
Computational Intelligence ◽  
Intelligent Systems ◽  
Manufacturing Systems ◽  
Current Issue ◽  
Multi Agent Systems ◽  
Special Issue ◽  
Tokyo Institute ◽  
Institute Of Technology

SCIS & ISIS is a biennial international joint conference in the field of soft computing and intelligent systems, including branches of researches from fuzzy systems, neural networks, evolutionary computation, multi-agent systems, artificial intelligence or robotics. SCIS & ISIS 2006 falls on the 3rd International Conference on Soft Computing and Intelligent Systems (SCIS) and the 7th International Symposium on Advanced Intelligent Systems (ISIS) held at Tokyo Institute of Technology, in Tokyo, Japan, on September 20-24, 2006. In this conference, 464 original papers were accepted for presentation and the number of attendees was 526. After preliminary selection and review made by the session chairs and the International Program Committees of SCIS & ISIS 2006, we have selected more than 50 papers to be published in extended form in the Special Issue of the Journal of Advanced Computational Intelligence and Intelligent Informatics. The accepted papers are published as the special issues in Vol.11, No.6, 7, and 8 in 2007. This current issue presents 23 papers and covers most of the topics of the conference including fuzzy theories, self-organizing maps, and the optimization of neural networks. The learning and search methods in computational intelligence and real-world applications to image processing, robotics and manufacturing systems are highlighted in this current issue. I would like to thank all the authors and reviewers for their contribution to make this special issue possible. I am also grateful to Prof. Toshio Fukuda, Nagoya University and Prof. Kaoru Hirota, Tokyo Institute of Technology, Editors-in-chief, for inviting me to serve as Guest Editor of this Journal.

Selected Papers from SCIS & ISIS 2008 – No.1

2009 ◽  
Vol 13 (3) ◽  
pp. 171-171
Author(s):  
Tsuyoshi Nakamura ◽  
Keyword(s):  
Soft Computing ◽  
Fuzzy Systems ◽  
Intelligent Systems ◽  
Current Issue ◽  
Fuzzy Theory ◽  
Special Issue ◽  
Self Organizing Maps ◽  
Tokyo Institute ◽  
Institute Of Technology ◽  
And Robotics

Welcome to this special issue of the Journal of Advanced Computational Intelligence and Intelligent Informatics (JACIII). I am pleased to introduce 41 selected papers presented at the 3rd International Conference on Soft Computing and Intelligent Systems (SCIS) and the 7th International Symposium on Advanced Intelligent Systems (ISIS) held on September 17-21, 2008, at Nagoya University in Nagoya, Japan. This conference featured 401 original papers in presentations attended by some 500 participants. SCIS & ISIS is a biennial international joint conference in the field of soft computing and intelligent systems, including branches of research ranging from fuzzy systems, neural networks, and evolutionary computation to multiagent systems, artificial intelligence, and robotics. This current issue presents 20 papers covering most of the conference topics including fuzzy theory, self-organizing maps, robotics, computer vision, and optimization algorithms. I would like to thank the authors and reviewers and SCIS & ISIS 2008 for making this special issue possible. I am also grateful to Prof. Toshio Fukuda, Nagoya University, and Prof. Kaoru Hirota, Tokyo Institute of Technology, the editors-in-chief, and the SCIS & ISIS 2008 conference staff for inviting me to guest-edit this Journal.

Advanced Computational Intelligence in Control Theory and Applications

1999 ◽  
Vol 3 (2) ◽  
pp. 67-67
Author(s):  
Kazuo Tanaka ◽  
Keyword(s):  
Neural Networks ◽  
Genetic Algorithms ◽  
Fuzzy Logic ◽  
Control Theory ◽  
Soft Computing ◽  
Computational Intelligence ◽  
Intelligent Systems ◽  
Special Issue ◽  
Systems And Control ◽  
And Control

We are witnessing a rapidly growing interest in the field of advanced computational intelligence, a "soft computing" technique. As Prof. Zadeh has stated, soft computing integrates fuzzy logic, neural networks, evolutionary computation, and chaos. Soft computing is the most important technology available for designing intelligent systems and control. The difficulties of fuzzy logic involve acquiring knowledge from experts and finding knowledge for unknown tasks. This is related to design problems in constructing fuzzy rules. Neural networks and genetic algorithms are attracting attention for their potential in raising the efficiency of knowledge finding and acquisition. Combining the technologies of fuzzy logic and neural networks and genetic algorithms, i.e., soft computing techniques will have a tremendous impact on the fields of intelligent systems and control design. To explain the apparent success of soft computing, we must determine the basic capabilities of different soft computing frameworks. Give the great amount of research being done in these fields, this issue addresses fundamental capabilities. This special issue is devoted to advancing computational intelligence in control theory and applications. It contains nine excellent papers dealing with advanced computational intelligence in control theory and applications such as fuzzy control and stability, mobile robot control, neural networks, gymnastic bar action, petroleum plant control, genetic programming, Petri net, and modeling and prediction of complex systems. As editor of this special issue, I believe that the excellent research results it contains provide the basis for leadership in coming research on advanced computational intelligence in control theory and applications.

Special Issue on Papers Selected in ISIS & SCIS 2003

2004 ◽  
Vol 8 (4) ◽  
pp. 349-349
Author(s):  
Yong-Soo Kim ◽  
◽  
Kwee-Bo Sim ◽  
Keyword(s):  
Neural Networks ◽  
Image Processing ◽  
Genetic Algorithms ◽  
Soft Computing ◽  
Intelligent Control ◽  
Intelligent Systems ◽  
Fuzzy Controller ◽  
Intelligent System ◽  
Wide Spectrum ◽  
Special Issue

This special issue of journal covers a broad field ranging from intelligent systems to robotics. These papers were selected among the papers that were presented at the Joint 4th International Symposium on Advanced Intelligent Systems and 2nd International Conference on Soft Computing and Intelligent Systems which was held in Jeju, Korea on September 25-28, 2003. In the above symposium, there was a wide spectrum of intelligent systems and related topics, including sessions: intelligent systems, intelligent control, fuzzy sets, fuzzy systems, neural networks, robotics, genetic algorithms, image processing, soft computing, artificial life, etc. Many interesting results were presented at the symposium. Among these various papers, this special issue offers a selection of sixteen papers that contribute to advances of intelligent systems in various aspects. The topics that the selected papers deal with are fuzzy controller for the mobile robot control, neural networks and their application to image processing, intelligent control for a robot, intelligent system for probe detection, fuzzy image processing, genetic algorithms, fuzzy clustering for incomplete categorical data, predictive fuzzy controller for an electric four-wheeled vehicle. As guest editors of this special issue, we would like to express our thanks to authors for their contribution, the anonymous referees for their review, and Prof. Kaoru Hirota for his giving the opportunity to publish this special issue.

EDITORIAL

2012 ◽  
Vol 21 (03) ◽  
pp. 1202002
Author(s):  
ZHIHUA CUI ◽  
ZHONGZHI SHI ◽  
RAJAN ALEX
Keyword(s):  
Swarm Intelligence ◽  
Decentralized Control ◽  
Intelligent Systems ◽  
Wide Spectrum ◽  
Self Organization ◽  
Multi Agent Systems ◽  
Special Issue ◽  
Agent Systems ◽  
The World ◽  
Multi Agent

Swarm intelligence is an umbrella for amount optimization algorithms. This discipline deals with natural and artificial systems composed of many individuals that coordinate their activities using decentralized control and self-organization. In general, multi-agent systems that use some swarm intelligence are said to be swarm intelligent systems. They are mostly used as search engines and optimization tools. The goal of this special issue has been to offer a wide spectrum of sample works throughout the world about innovative methodologies of swarm intelligence. The issue should be useful both for beginners and experienced researchers in the field of computational intelligence.

Foundations for Knowledge and Belief Management

2021 ◽  
Vol 17 (3) ◽  
pp. 88-99
Author(s):  
Roderic A. Girle
Keyword(s):  
Intelligent Systems ◽  
Turing Test ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Conceptual Structures ◽  
Interacting Agents ◽  
Questions And Answers ◽  
Multi Agent ◽  
The Difference ◽  
Dialogue Theory

Three foundational principles are introduced: intelligent systems such as those that would pass the Turing test should display multi-agent or interactional intelligence; multi-agent systems should be based on conceptual structures common to all interacting agents, machine and human; and multi-agent systems should have an underlying interactional logic such as dialogue logic. In particular, a multi-agent rather than an orthodox analysis of the key concepts of knowledge and belief is discussed. The contrast that matters is the difference between the different questions and answers about the support for claims to know and claims to believe. A simple multi-agent system based on dialogue theory which provides for such a difference is set out.

scholarly journals Agents’ ontologies negotiation in cohesive hybrid intelligent multi-agent systems

2021 ◽  
Vol 2094 (3) ◽  
pp. 032033
Author(s):  
I A Kirikov ◽  
S V Listopad ◽  
A S Luchko
Keyword(s):  
Intelligent Agents ◽  
Intelligent Systems ◽  
Multi Agent Systems ◽  
Labor Costs ◽  
Joint Work ◽  
Working Process ◽  
Agent Systems ◽  
Development Teams ◽  
Multi Agent ◽  
Domain Models

Abstract The paper proposes the model for negotiating intelligent agents’ ontologies in cohesive hybrid intelligent multi-agent systems. Intelligent agent in this study will be called relatively autonomous software entity with developed domain models and goal-setting mechanisms. When such agents have to work together within single hybrid intelligent multi-agent systems to solve some problem, the working process “go wild”, if there are significant differences between the agents’ “points of view” on the domain, goals and rules of joint work. In this regard, in order to reduce labor costs for integrating intelligent agents into a single system, the concept of cohesive hybrid intelligent multi-agent systems was proposed that implement mechanisms for negotiating goals, domain models and building a protocol for solving the problems posed. The presence of these mechanisms is especially important when building intelligent systems from intelligent agents created by various independent development teams.

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